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Agents and Data Mining Interaction: 9th International Workshop, ADMI 2013, Saint Paul, MN, USA, May 6-7, 2013, Revised Selected Papers 2014 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 137 pages, kõrgus x laius: 235x155 mm, kaal: 454 g, 45 Illustrations, black and white; IX, 137 p. 45 illus., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 8316
  • Ilmumisaeg: 21-May-2014
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642551912
  • ISBN-13: 9783642551918
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Agents and Data Mining Interaction: 9th International Workshop, ADMI 2013, Saint Paul, MN, USA, May 6-7, 2013, Revised Selected Papers 2014 ed.Suurem pilt
  • Formaat: Paperback / softback, 137 pages, kõrgus x laius: 235x155 mm, kaal: 454 g, 45 Illustrations, black and white; IX, 137 p. 45 illus., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 8316
  • Ilmumisaeg: 21-May-2014
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642551912
  • ISBN-13: 9783642551918
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783642551918.html
Märksõnad:
This book constitutes the thoroughly refereed and revised selected papers from the 9th International Workshop on Agents and Data Mining Interaction, ADMI 2013, held in Saint Paul, MN, USA in May 2013. The 10 papers presented in this volume were carefully selected for inclusion in the book and are organized in topical sections named agent mining and data mining.
Using Dynamic Bayesian Networks to Model User-Experience.- Multi-Agent Joint Learning from Argumentation.- Towards Mining Norms in Open Source Software Repositories.- The Recognition of Multiple Virtual Identities Association Based on Multi-Agent System.- Redundant Feature Selection for Telemetry Data.- Mining Emerging Patterns of PIU from Computer-Mediated Interaction Events.- Learning Heterogeneous Coupling Relationships between Non-IID Terms.- Learning the Hotness of Information Discussions with Multi-Dimensional Hawkes Processes.- A Spectral Clustering Algorithm Based on Hierarchical Method.- Transitive Identity Mapping using Force-Based Clustering.